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BlueBrain / atlas-densities

Tools to compute densities in the context of brain atlases.
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Nsetm 2196 update output #41

Closed edasubert closed 1 year ago

codecov-commenter commented 1 year ago

Codecov Report

Merging #41 (6a2c1fa) into NSETM-2196-multiple-probability-maps (4ffd4bb) will decrease coverage by 0.05%. The diff coverage is 96.29%.

@@                           Coverage Diff                            @@
##           NSETM-2196-multiple-probability-maps      #41      +/-   ##
========================================================================
- Coverage                                 97.79%   97.74%   -0.05%     
========================================================================
  Files                                        22       22              
  Lines                                      1360     1377      +17     
========================================================================
+ Hits                                       1330     1346      +16     
- Misses                                       30       31       +1
Flag Coverage Δ
pytest 97.74% <96.29%> (-0.05%) :arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files Coverage Δ
...ities/densities/mtype_densities_from_map/create.py 98.00% <96.29%> (-2.00%) :arrow_down:
edasubert commented 1 year ago

example output legend:

{
    "BP": {
        "bAC": "data/ccfv2/test_regions_me-types/BP|bAC_densities.nrrd",
        "bIR": "data/ccfv2/test_regions_me-types/BP|bIR_densities.nrrd",
        "bNAC": "data/ccfv2/test_regions_me-types/BP|bNAC_densities.nrrd",
        "cAC": "data/ccfv2/test_regions_me-types/BP|cAC_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/BP|cNAC_densities.nrrd",
        "dSTUT": "data/ccfv2/test_regions_me-types/BP|dSTUT_densities.nrrd"
    },
    "BTC": {
        "bAC": "data/ccfv2/test_regions_me-types/BTC|bAC_densities.nrrd",
        "bIR": "data/ccfv2/test_regions_me-types/BTC|bIR_densities.nrrd",
        "bNAC": "data/ccfv2/test_regions_me-types/BTC|bNAC_densities.nrrd",
        "cAC": "data/ccfv2/test_regions_me-types/BTC|cAC_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/BTC|cNAC_densities.nrrd",
        "bSTUT": "data/ccfv2/test_regions_me-types/BTC|bSTUT_densities.nrrd",
        "dNAC": "data/ccfv2/test_regions_me-types/BTC|dNAC_densities.nrrd"
    },
    "ChC": {
        "cAC": "data/ccfv2/test_regions_me-types/ChC|cAC_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/ChC|cNAC_densities.nrrd",
        "dNAC": "data/ccfv2/test_regions_me-types/ChC|dNAC_densities.nrrd"
    },
    "DBC": {
        "bAC": "data/ccfv2/test_regions_me-types/DBC|bAC_densities.nrrd",
        "bIR": "data/ccfv2/test_regions_me-types/DBC|bIR_densities.nrrd",
        "bNAC": "data/ccfv2/test_regions_me-types/DBC|bNAC_densities.nrrd",
        "cAC": "data/ccfv2/test_regions_me-types/DBC|cAC_densities.nrrd",
        "bSTUT": "data/ccfv2/test_regions_me-types/DBC|bSTUT_densities.nrrd",
        "cIR": "data/ccfv2/test_regions_me-types/DBC|cIR_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/DBC|cNAC_densities.nrrd"
    },
    "LBC": {
        "bAC": "data/ccfv2/test_regions_me-types/LBC|bAC_densities.nrrd",
        "bNAC": "data/ccfv2/test_regions_me-types/LBC|bNAC_densities.nrrd",
        "cAC": "data/ccfv2/test_regions_me-types/LBC|cAC_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/LBC|cNAC_densities.nrrd",
        "cSTUT": "data/ccfv2/test_regions_me-types/LBC|cSTUT_densities.nrrd",
        "dNAC": "data/ccfv2/test_regions_me-types/LBC|dNAC_densities.nrrd",
        "dSTUT": "data/ccfv2/test_regions_me-types/LBC|dSTUT_densities.nrrd",
        "cIR": "data/ccfv2/test_regions_me-types/LBC|cIR_densities.nrrd",
        "bIR": "data/ccfv2/test_regions_me-types/LBC|bIR_densities.nrrd",
        "bSTUT": "data/ccfv2/test_regions_me-types/LBC|bSTUT_densities.nrrd"
    },
    "MC": {
        "bAC": "data/ccfv2/test_regions_me-types/MC|bAC_densities.nrrd",
        "bNAC": "data/ccfv2/test_regions_me-types/MC|bNAC_densities.nrrd",
        "cAC": "data/ccfv2/test_regions_me-types/MC|cAC_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/MC|cNAC_densities.nrrd",
        "dNAC": "data/ccfv2/test_regions_me-types/MC|dNAC_densities.nrrd",
        "bIR": "data/ccfv2/test_regions_me-types/MC|bIR_densities.nrrd",
        "bSTUT": "data/ccfv2/test_regions_me-types/MC|bSTUT_densities.nrrd",
        "cSTUT": "data/ccfv2/test_regions_me-types/MC|cSTUT_densities.nrrd",
        "cIR": "data/ccfv2/test_regions_me-types/MC|cIR_densities.nrrd"
    },
    "NBC": {
        "bAC": "data/ccfv2/test_regions_me-types/NBC|bAC_densities.nrrd",
        "bNAC": "data/ccfv2/test_regions_me-types/NBC|bNAC_densities.nrrd",
        "cAC": "data/ccfv2/test_regions_me-types/NBC|cAC_densities.nrrd",
        "cIR": "data/ccfv2/test_regions_me-types/NBC|cIR_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/NBC|cNAC_densities.nrrd",
        "dNAC": "data/ccfv2/test_regions_me-types/NBC|dNAC_densities.nrrd",
        "bIR": "data/ccfv2/test_regions_me-types/NBC|bIR_densities.nrrd",
        "bSTUT": "data/ccfv2/test_regions_me-types/NBC|bSTUT_densities.nrrd",
        "cSTUT": "data/ccfv2/test_regions_me-types/NBC|cSTUT_densities.nrrd",
        "dSTUT": "data/ccfv2/test_regions_me-types/NBC|dSTUT_densities.nrrd"
    },
    "NGC": {
        "bNAC": "data/ccfv2/test_regions_me-types/NGC|bNAC_densities.nrrd",
        "cAC": "data/ccfv2/test_regions_me-types/NGC|cAC_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/NGC|cNAC_densities.nrrd",
        "cSTUT": "data/ccfv2/test_regions_me-types/NGC|cSTUT_densities.nrrd"
    },
    "SBC": {
        "bNAC": "data/ccfv2/test_regions_me-types/SBC|bNAC_densities.nrrd",
        "cAC": "data/ccfv2/test_regions_me-types/SBC|cAC_densities.nrrd",
        "dNAC": "data/ccfv2/test_regions_me-types/SBC|dNAC_densities.nrrd"
    },
    "DAC": {
        "bNAC": "data/ccfv2/test_regions_me-types/DAC|bNAC_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/DAC|cNAC_densities.nrrd"
    },
    "DLAC": {
        "cNAC": "data/ccfv2/test_regions_me-types/DLAC|cNAC_densities.nrrd"
    },
    "HAC": {
        "bNAC": "data/ccfv2/test_regions_me-types/HAC|bNAC_densities.nrrd",
        "cIR": "data/ccfv2/test_regions_me-types/HAC|cIR_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/HAC|cNAC_densities.nrrd"
    },
    "NGC-DA": {
        "bNAC": "data/ccfv2/test_regions_me-types/NGC-DA|bNAC_densities.nrrd",
        "cAC": "data/ccfv2/test_regions_me-types/NGC-DA|cAC_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/NGC-DA|cNAC_densities.nrrd",
        "cSTUT": "data/ccfv2/test_regions_me-types/NGC-DA|cSTUT_densities.nrrd"
    },
    "NGC-SA": {
        "cNAC": "data/ccfv2/test_regions_me-types/NGC-SA|cNAC_densities.nrrd"
    },
    "SLAC": {
        "bNAC": "data/ccfv2/test_regions_me-types/SLAC|bNAC_densities.nrrd",
        "cAC": "data/ccfv2/test_regions_me-types/SLAC|cAC_densities.nrrd",
        "cNAC": "data/ccfv2/test_regions_me-types/SLAC|cNAC_densities.nrrd"
    }
}
mgeplf commented 1 year ago

Nice! output looks like it makes sense.

lecriste commented 1 year ago

Nice! output looks like it makes sense.

@mgeplf, the usage of this output legend is to get the M and E type of a given file. Can we reverse the dictionary? Something like:

{
  "filename_0": ["Mtype_0", "EType_0"],
  "filename_1": ["Mtype_1", "EType_1"],
  ...
}
mgeplf commented 1 year ago

We could, but it's also feasable to transform it with:

b = {f: (m, e) for m, mv in a.items() for e, f in mv.items()}

where a is the dictionary.